Extracellular fluxes and gene expression data are easily measured and have been obtained for a wide variety of organisms and applications. However, it is difficult to incorporate these data directly into computational models to predict intracellular flux distributions. Central metabolic fluxes can instead be quantified using carbon isotope-based (i.e., 13C) metabolic flux analysis (MFA). MFA data, however, can be costly to obtain directly, and published data is available for only a few organisms.
Flux balance analysis (FBA) is a mathematical method for simulating metabolism in genome scale reconstructions of metabolic networks. FBA is often used to predict flux distributions that maximize biomass, and parsimonious FBA (pFBA) predicts flux distributions that additionally minimize the sum total of metabolic fluxes. When compared to MFA, FBA is less intensive in terms of the input data required for constructing the model (i.e., does not require 13C-based pathway fluxes), is computationally inexpensive, and can calculate steady-state metabolic fluxes for large models in just a few seconds. However, FBA predictions do not always match experimentally measured fluxes.
FBA is also used in bioprocess engineering to systematically identify modifications to the metabolic networks of microbes used in fermentation processes that improve product yields of industrially important chemicals (e.g., ethanol, succinic acid, etc.). When simulating knockouts or growth on media, FBA predicts a steady-state flux distribution that is more consistent with adaptively evolved strains, which can be reached over varying timescales (e.g., 40 days, 700 generations, etc.). Alternatives to FBA—including MOMA, ROOM, and RELATCH—can better predict the immediate effect of an environmental perturbation or gene deletion. While more accurate, these FBA alternatives rely heavily upon the flux estimates for the parental strain. As a result, incorrect parental strain fluxes (i.e., starting point) can lead to significant errors in estimates for mutants derived from the parental strain. A need exists for a method with improved identification of parental strain fluxes that does not require MFA.
Systems and methods that address the above-mentioned problems are needed.